|Publication number||US8588517 B2|
|Application number||US 13/742,094|
|Publication date||19 Nov 2013|
|Filing date||15 Jan 2013|
|Priority date||18 Dec 2009|
|Also published as||US8374423, US20110150271, US20120177254, US20130129155|
|Publication number||13742094, 742094, US 8588517 B2, US 8588517B2, US-B2-8588517, US8588517 B2, US8588517B2|
|Inventors||Johnny Lee, Tommer Leyvand, Craig Peeper|
|Original Assignee||Microsoft Corporation|
|Export Citation||BiBTeX, EndNote, RefMan|
|Patent Citations (201), Non-Patent Citations (40), Referenced by (5), Classifications (7), Legal Events (3)|
|External Links: USPTO, USPTO Assignment, Espacenet|
This application is a continuation application of U.S. application Ser. No. 13/410,546, “MOTION DETECTION USING DEPTH IMAGES,” filed on Mar. 2, 2012, which is a continuation application of U.S. application Ser. No. 12/641,788, “MOTION DETECTION USING DEPTH IMAGES,” filed on Dec. 18, 2009, both of which are incorporated herein by reference in its entirety.
Many computing applications such as computer games, multimedia applications, or the like use controls to allow users to manipulate game characters or other aspects of an application. Typically such controls are input using, for example, controllers, remotes, keyboards, mice, or the like. Unfortunately, such controls can be difficult to learn, thus creating a barrier between a user and such games and applications. Furthermore, such controls may be different than actual game actions or other application actions for which the controls are used. For example, a game control that causes a game character to swing a baseball bat may not correspond to an actual motion of swinging the baseball bat.
Disclosed herein are systems and methods for tracking motion of a user or other objects in a scene using depth images. The tracked motion is then used to update an application. Therefore, a user can manipulate game characters or other aspects of the application by using movement of the user's body and/or objects around the user, rather than (or in addition to) using controllers, remotes, keyboards, mice, or the like.
A sensor system creates a sequence of depth images that are used to detect and track motion of objects within range of the sensor system. A reference image is created and updated based on a moving average (or other function) of a set of depth images. A new depth images is compared to the reference image to create a motion image, which is an image file (or other data structure) with data representing motion. The new depth image is also used to update the reference image. The data in the motion image is grouped and associated with one or more objects being tracked. The tracking of the objects is updated by the grouped data in the motion image. The new positions of the objects are used to update an application. For example, a video game system will update the position of images displayed in the video based on the new positions of the objects. In one implementation, avatars can be moved based on movement of the user in front of a camera.
One embodiment includes creating a reference image that includes foreground data and background data based on multiple previous depth images, receiving a new depth image, creating a motion image based on the new depth image and the reference image, identifying one or more objects in the motion image, using position information for the identified one or more objects to update an application, and updating the reference image based on the new depth image.
One embodiment includes a communication interface that receives depth images, one or more storage devices that store depth images, a display interface, and one or more processors in communication with the one or more storage devices and the display interface. The one or more processors access a new depth image received from the communication interface and identify motion based comparing the new depth image to a reference image stored in the one or more storage devices. The one or more processors create a motion image representing identified motion. The one or more processors group pixels of the motion image and associate one or more groups of pixels with one or more objects identified in object history data stored in the one or more storage devices. The one or more processors use position information for the identified one or more objects to update an application running on the apparatus and provide signals on the display interface that indicate the update to the application.
One embodiment includes receiving a new depth image, identifying motion based on comparing the new depth image to a reference image, creating a motion image representing identified forward motion and discarding identified backward motion when creating the motion image, identifying one or more objects in the motion image, and reporting the identified one or more objects in the motion image.
This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter. Furthermore, the claimed subject matter is not limited to implementations that solve any or all disadvantages noted in any part of this disclosure.
Depth images are captured by a sensor and used by a computing system to track motions of a user and/or other objects. The tracked motion is then used to update an application. Therefore, a user can manipulate game characters or other aspects of the application by using movement of the user's body and/or objects around the user, rather than (or in addition to) using controllers, remotes, keyboards, mice, or the like. For example, a video game system will update the position of images displayed in the video based on the new positions of the objects or update an avatar based on motion of the user.
As shown in
As shown in
According to one embodiment, the tracking system 10 may be connected to an audiovisual device 16 such as a television, a monitor, a high-definition television (HDTV), or the like that may provide game or application visuals and/or audio to a user such as the user 18. For example, the computing system 12 may include a video adapter such as a graphics card and/or an audio adapter such as a sound card that may provide audiovisual signals associated with the game application, non-game application, or the like. The audiovisual device 16 may receive the audiovisual signals from the computing system 12 and may then output the game or application visuals and/or audio associated with the audiovisual signals to the user 18. According to one embodiment, the audiovisual device 16 may be connected to the computing system 12 via, for example, an S-Video cable, a coaxial cable, an HDMI cable, a DVI cable, a VGA cable, component video cable, or the like.
As shown in
In the example depicted in
Other movements by the user 18 may also be interpreted as other controls or actions and/or used to animate the player avatar, such as controls to bob, weave, shuffle, block, jab, or throw a variety of different power punches. Furthermore, some movements may be interpreted as controls that may correspond to actions other than controlling the player avatar 40. For example, in one embodiment, the player may use movements to end, pause, or save a game, select a level, view high scores, communicate with a friend, etc. According to another embodiment, the player may use movements to select the game or other application from a main user interface. Thus, in example embodiments, a full range of motion of the user 18 may be available, used, and analyzed in any suitable manner to interact with an application.
In example embodiments, the human target such as the user 18 may have an object. In such embodiments, the user of an electronic game may be holding the object such that the motions of the player and the object may be used to adjust and/or control parameters of the game. For example, the motion of a player holding a racket may be tracked and utilized for controlling an on-screen racket in an electronic sports game. In another example embodiment, the motion of a player holding an object may be tracked and utilized for controlling an on-screen weapon in an electronic combat game. Objects not held by the user can also be tracked, such as objects thrown, pushed or rolled by the user (or a different user) as well as self propelled objects. In addition to boxing, other games can also be implemented.
According to other example embodiments, the tracking system 10 may further be used to interpret target movements as operating system and/or application controls that are outside the realm of games. For example, virtually any controllable aspect of an operating system and/or application may be controlled by movements of the target such as the user 18.
As shown in
As shown in
According to another example embodiment, time-of-flight analysis may be used to indirectly determine a physical distance from the capture device 20 to a particular location on the targets or objects by analyzing the intensity of the reflected beam of light over time via various techniques including, for example, shuttered light pulse imaging.
In another example embodiment, the capture device 20 may use a structured light to capture depth information. In such an analysis, patterned light (i.e., light displayed as a known pattern such as grid pattern, a stripe pattern, or different pattern) may be projected onto the scene via, for example, the IR light component 24. Upon striking the surface of one or more targets or objects in the scene, the pattern may become deformed in response. Such a deformation of the pattern may be captured by, for example, the 3-D camera 26 and/or the RGB camera 28 and may then be analyzed to determine a physical distance from the capture device to a particular location on the targets or objects. In some implementations, the IR Light component 24 is displaced from the cameras 24 and 26 so triangulation can be used to determined distance from cameras 24 and 26. In some implementations, the capture device 20 will include a dedicated IR sensor to sense the IR light.
According to another embodiment, the capture device 20 may include two or more physically separated cameras that may view a scene from different angles to obtain visual stereo data that may be resolved to generate depth information. Other types of depth image sensors can also be used to create a depth image.
The capture device 20 may further include a microphone 30. The microphone 30 may include a transducer or sensor that may receive and convert sound into an electrical signal. According to one embodiment, the microphone 30 may be used to reduce feedback between the capture device 20 and the computing system 12 in the target recognition, analysis, and tracking system 10. Additionally, the microphone 30 may be used to receive audio signals that may also be provided by the user to control applications such as game applications, non-game applications, or the like that may be executed by the computing system 12.
In an example embodiment, the capture device 20 may further include a processor 32 that may be in operative communication with the image camera component 22. The processor 32 may include a standardized processor, a specialized processor, a microprocessor, or the like that may execute instructions including, for example, instructions for receiving a depth image, generating the appropriate data format (e.g., frame) and transmitting the data to computing system 12.
The capture device 20 may further include a memory component 34 that may store the instructions that may be executed by the processor 32, images or frames of images captured by the 3-D camera and/or RGB camera, or any other suitable information, images, or the like. According to an example embodiment, the memory component 34 may include random access memory (RAM), read only memory (ROM), cache, Flash memory, a hard disk, or any other suitable storage component. As shown in
As shown in
Computing system 12 includes gestures library 190, structure data 192, depth image processing and object reporting module 194 and application 196. Depth image processing and object reporting module 194 uses the depth images to track motion of objects, such as the user and other objects. To assist in the tracking of the objects, depth image processing and object reporting module 194 uses gestures library 190 and structure data 192.
Structure data 192 includes structural information about objects that may be tracked. For example, a skeletal model of a human may be stored to help understand movements of the user and recognize body parts. Structural information about inanimate objects may also be stored to help recognize those objects and help understand movement.
Gestures library 190 may include a collection of gesture filters, each comprising information concerning a gesture that may be performed by the skeletal model (as the user moves). The data captured by the cameras 26, 28 and the capture device 20 in the form of the skeletal model and movements associated with it may be compared to the gesture filters in the gesture library 190 to identify when a user (as represented by the skeletal model) has performed one or more gestures. Those gestures may be associated with various controls of an application. Thus, the computing system 12 may use the gestures library 190 to interpret movements of the skeletal model and to control application 196 based on the movements. As such, gestures library may be used by depth image processing and object reporting module 194 and application 196.
Application 196 can be a video game, productivity application, etc. In one embodiment, depth image processing and object reporting module 194 will report to application 196 an identification of each object detected and the location of the object for each frame. Application 196 will use that information to update the position or movement of an avatar or other images in the display.
A graphics processing unit (GPU) 108 and a video encoder/video codec (coder/decoder) 114 form a video processing pipeline for high speed and high resolution graphics processing. Data is carried from the graphics processing unit 108 to the video encoder/video codec 114 via a bus. The video processing pipeline outputs data to an A/V (audio/video) port 140 for transmission to a television or other display. A memory controller 110 is connected to the GPU 108 to facilitate processor access to various types of memory 112, such as, but not limited to, a RAM (Random Access Memory).
The multimedia console 100 includes an I/O controller 120, a system management controller 122, an audio processing unit 123, a network interface controller 124, a first USB host controller 126, a second USB controller 128 and a front panel I/O subassembly 130 that are preferably implemented on a module 118. The USB controllers 126 and 128 serve as hosts for peripheral controllers 142(1)-142(2), a wireless adapter 148, and an external memory device 146 (e.g., flash memory, external CD/DVD ROM drive, removable media, etc.). The network interface 124 and/or wireless adapter 148 provide access to a network (e.g., the Internet, home network, etc.) and may be any of a wide variety of various wired or wireless adapter components including an Ethernet card, a modem, a Bluetooth module, a cable modem, and the like.
System memory 143 is provided to store application data that is loaded during the boot process. A media drive 144 is provided and may comprise a DVD/CD drive, Blu-Ray drive, hard disk drive, or other removable media drive, etc. The media drive 144 may be internal or external to the multimedia console 100. Application data may be accessed via the media drive 144 for execution, playback, etc. by the multimedia console 100. The media drive 144 is connected to the I/O controller 120 via a bus, such as a Serial ATA bus or other high speed connection (e.g., IEEE 1394).
The system management controller 122 provides a variety of service functions related to assuring availability of the multimedia console 100. The audio processing unit 123 and an audio codec 132 form a corresponding audio processing pipeline with high fidelity and stereo processing. Audio data is carried between the audio processing unit 123 and the audio codec 132 via a communication link. The audio processing pipeline outputs data to the A/V port 140 for reproduction by an external audio player or device having audio capabilities.
The front panel I/O subassembly 130 supports the functionality of the power button 150 and the eject button 152, as well as any LEDs (light emitting diodes) or other indicators exposed on the outer surface of the multimedia console 100. A system power supply module 136 provides power to the components of the multimedia console 100. A fan 138 cools the circuitry within the multimedia console 100.
The CPU 101, GPU 108, memory controller 110, and various other components within the multimedia console 100 are interconnected via one or more buses, including serial and parallel buses, a memory bus, a peripheral bus, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures can include a Peripheral Component Interconnects (PCI) bus, PCI-Express bus, etc.
When the multimedia console 100 is powered ON, application data may be loaded from the system memory 143 into memory 112 and/or caches 102, 104 and executed on the CPU 101. The application may present a graphical user interface that provides a consistent user experience when navigating to different media types available on the multimedia console 100. In operation, applications and/or other media contained within the media drive 144 may be launched or played from the media drive 144 to provide additional functionalities to the multimedia console 100.
The multimedia console 100 may be operated as a standalone system by simply connecting the system to a television or other display. In this standalone mode, the multimedia console 100 allows one or more users to interact with the system, watch movies, or listen to music. However, with the integration of broadband connectivity made available through the network interface 124 or the wireless adapter 148, the multimedia console 100 may further be operated as a participant in a larger network community.
When the multimedia console 100 is powered ON, a set amount of hardware resources are reserved for system use by the multimedia console operating system. These resources may include a reservation of memory (e.g., 16 MB), CPU and GPU cycles (e.g., 5%), networking bandwidth (e.g., 8 kbs), etc. Because these resources are reserved at system boot time, the reserved resources do not exist from the application's view.
In particular, the memory reservation preferably is large enough to contain the launch kernel, concurrent system applications and drivers. The CPU reservation is preferably constant such that if the reserved CPU usage is not used by the system applications, an idle thread will consume any unused cycles.
With regard to the GPU reservation, lightweight messages generated by the system applications (e.g., popups) are displayed by using a GPU interrupt to schedule code to render popup into an overlay. The amount of memory required for an overlay depends on the overlay area size and the overlay preferably scales with screen resolution. Where a full user interface is used by the concurrent system application, it is preferable to use a resolution independent of application resolution. A scaler may be used to set this resolution such that the need to change frequency and cause a TV resynch is eliminated.
After the multimedia console 100 boots and system resources are reserved, concurrent system applications execute to provide system functionalities. The system functionalities are encapsulated in a set of system applications that execute within the reserved system resources described above. The operating system kernel identifies threads that are system application threads versus gaming application threads. The system applications are preferably scheduled to run on the CPU 101 at predetermined times and intervals in order to provide a consistent system resource view to the application. The scheduling is to minimize cache disruption for the gaming application running on the console.
When a concurrent system application requires audio, audio processing is scheduled asynchronously to the gaming application due to time sensitivity. A multimedia console application manager (described below) controls the gaming application audio level (e.g., mute, attenuate) when system applications are active.
Input devices (e.g., controllers 142(1) and 142(2)) are shared by gaming applications and system applications. The input devices are not reserved resources, but are to be switched between system applications and the gaming application such that each will have a focus of the device. The application manager preferably controls the switching of input stream, without knowledge the gaming application's knowledge and a driver maintains state information regarding focus switches. The cameras 26, 28 and capture device 20 may define additional input devices for the console 100 via USB controller 126 or other interface.
Computing system 220 comprises a computer 241, which typically includes a variety of computer readable media. Computer readable media can be any available media that can be accessed by computer 241 and includes both volatile and nonvolatile media, removable and non-removable media. The system memory 222 includes computer storage media in the form of volatile and/or nonvolatile memory such as read only memory (ROM) 223 and random access memory (RAM) 260. A basic input/output system 224 (BIOS), containing the basic routines that help to transfer information between elements within computer 241, such as during start-up, is typically stored in ROM 223. RAM 260 typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by processing unit 259. By way of example, and not limitation,
The computer 241 may also include other removable/non-removable, volatile/nonvolatile computer storage media. By way of example only,
The drives and their associated computer storage media discussed above and illustrated in
The computer 241 may operate in a networked environment using logical connections to one or more remote computers, such as a remote computer 246. The remote computer 246 may be a personal computer, a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to the computer 241, although only a memory storage device 247 has been illustrated in
When used in a LAN networking environment, the computer 241 is connected to the LAN 245 through a network interface or adapter 237. When used in a WAN networking environment, the computer 241 typically includes a modem 250 or other means for establishing communications over the WAN 249, such as the Internet. The modem 250, which may be internal or external, may be connected to the system bus 221 via the user input interface 236, or other appropriate mechanism. In a networked environment, program modules depicted relative to the computer 241, or portions thereof, may be stored in the remote memory storage device. By way of example, and not limitation,
As explained above, capture device 20 provides RGB images and depth images to computing system 12. The depth image may be a plurality of observed pixels where each observed pixel has an observed depth value. For example, the depth image may include a two-dimensional (2-D) pixel area of the captured scene where each pixel in the 2-D pixel area may have a depth value such as a length or distance in, for example, centimeters, millimeters, or the like of an object in the captured scene from the capture device.
In one embodiment, the depth image may be colorized or grayscale such that different colors or shades of the pixels of the depth image correspond to and/or visually depict different distances of the targets 404 from the capture device 20. Upon receiving the image, one or more high-variance and/or noisy depth values may be removed and/or smoothed from the depth image; portions of missing and/or removed depth information may be filled in and/or reconstructed; and/or any other suitable processing may be performed on the received depth image.
In step 462 of
The reference image is updated based on each new depth image that is received. In one example, it will take 120 frames before the reference image is established. In other embodiments, the reference image will be established with the first depth image and then each additional depth image will be added to the reference image until there are 120 depth images received, then the reference image will be updated by the most recent 120 images.
The Equation (1) below provides one example of a formula for creating a reference image:
Equation (1) is used to operate on each pixel of the reference image. The variable “t” is the number of frames included in the reference image. In one example, 120 frames are included (4 seconds of video at 30 frames per second). The variable “old average” is the pixel value in the reference image for the particular pixel under consideration. The variable “new data” is the corresponding pixel value in the new depth image received. The output “new average” is the new pixel value of the updated reference image. Equation 1 is performed for every pixel of the reference image. In this manner, the reference image is re-created each time it is updated.
In one alternative, the value of t in Equation (1) can be different if the motion is backward versus forward. For a particular pixel, the value of t can be 120 if the motion is forward and the value of t can be 30 if the motion is backward.
When using Equation (1), the system does not need to keep a buffer of the previous 120 frames of depth images. Only the current new depth image needs to be stored in a buffer as well as the reference image. If the system used a straight averaging process, then a buffer would need to keep the last 120 frames of depth images.
Step 462 includes creating a motion image based on the new depth image received in step 460 and the reference image discussed above. As explained above, in one embodiment, the depth image and the reference image have the same number of pixels. The motion image created in step 462 is also a file (or other data structure) with the same number of pixels in the same format as the depth image and reference image. In one embodiment, the motion image is created by subtracting the new depth image from the reference image on a pixel by pixel basis. Thus, a corresponding pixel in the depth image is subtracted from the corresponding pixel in the reference image and the result is stored as the corresponding pixel the motion image.
If the pixel value in the new depth image is the same as the pixel value in the reference image, then there is no motion detected for the pixel. If the difference between the reference image and the new depth image is positive, then there is motion towards capture device 20. If the difference between the reference image and the depth image is negative, then there is motion away from the capture device 20.
In one embodiment, the process for creating the motion image will compare a threshold to the difference between the reference image and new depth image, on a pixel-by-pixel basis, so that small variations will not be detected as motion. Additionally, some embodiments will discard backward motion data (away from the camera) and only report forward motion (toward the camera). In some implementation, the system will track the magnitude of the motion (e.g., the difference between the reference image pixel and depth image pixel), while in other embodiments, the system will only store a Boolean value in the motion image to indicate whether there is motion or not.
In the above discussion, the comparison between the newly received depth image and the reference image is a simple subtracting and thresholding of values. More sophisticated embodiments may use mean squared error, standard deviation, difference of means or other statistical measures to compare the two data sets. This comparison may be done at the image level, pixel level or some other intermediate granularity of the image.
In the above discussion, there was only one reference image that was maintained and compared against the newly received depth images. In other embodiments, the system can use more than one reference image. For example, the system can create and maintain two or more reference images that averaged the depth data over differing, or even randomized, time constants. Comparison against multiple reference images can increase likelihood that moving objects will be properly identified. In such an embodiment, the new depth image is compared against multiple reference images. Any motion detected from any other comparisons will be used to add a 1 to the appropriate pixel in the created motion image. Other schemes for comparing multiple reference images to a depth image can also be used.
Looking back at
Once regions of the depth image have been identified as moving, it is useful to segment them into individual groups and track their locations over time. If multiple objects are detected by the system, the output is a collection of pixels that have been identified as moving. To group these pixels into individual objects, the system can use a method of segmentation or grouping called connected component analysis. Neighboring pixels that are also identified as moving are considered connected and therefore part of the same group. Once all of the pixels have been accounted for, the result is a set of groups that represent potential moving objects in the scene. Alternative methods determining which pixels of part of the same group can also be used such as thresholding Euclidian 3D distance or surface distance. Another alternative is to use clustering methods where a fixed number of groups are hypothesized, pixels are associated with each hypothetical group, and then the overall hypothesis is scored based on how well it explained the data. Another method is to maintain the probability that a pixel belongs to each possible group rather than directly associating it with a single group. This may be valuable in scenarios where the tracking system that maintains group assignment between frames can handle ambiguity in pixel association making it more robust in some application scenarios.
Looking back at
Groups containing a small number of pixels may be the result of noise in the depth image that exceeds the threshold limit in the motion detection step. To further filter out interference from noise, one embodiment may require a minimum pixel count or minimum physical size of a group to perform further motion analysis.
Looking back at
In some embodiments, the depth image process and client reporting module 194 performing the association of step 804 will make use of the information in gestures library 190 or a structure data 192 to associate groups with objects. For example, based on known shapes, the system can correlate a group with an existing object. If an object being tracked is a person, external structure data can be used to identify the shape of a person which will help the system better associate a group of pixels in the motion image with the person. Additionally, if the system knows it has previously been tracking a person with an arm moving, the external structure data 192 and the gestures library 190 could teach the system about probable movement of an arm, leg or other body part so the system can more readily identify the object. Similarly, the system may be able to recognize an inanimate object such as a ball or tennis racket based on references or templates in structure data 192.
Step 806 attempts to assign every group to an object being tracked. In some embodiments, some groups may not be assignable. In one embodiment, any group that cannot be assigned to an object will be assumed to be a new object. In step 808, any unassociated groups have new objects created and these unassociated groups are assigned to the new objects.
If moving objects come into close proximity to each other they may appear to merge into a single region. In some applications, it may be desirable to try to separate the single region back into the individual objects based on previous observation. One embodiment includes segmenting the pixels based on their proximity to the center of the previous objects. Pixels are associated with whatever previous objects they were closest to. The distance metric may be as simple as Euclidian distance, surface distance or other representation of distance.
In step 810, the system determines whether two objects from a previous motion image have merged in the current motion image. That is, if there are two objects in the previous motion image and the current image has only one object in a similar or proximal location as the two objects in the previous image, the system can determine that the two objects have merged. If the system determines that there have not been objects that have merged, then the process continues at step 812 and the object history data discussed above is updated so that all groups in the current motion image have their center coordinates (x,y) used to update the position of the objects being tracked. If, in step 810, the system determines that the two objects have merged, then the objects are separated by grouping the pixels based on proximity to the separate objects in the previous motion images in step 814. In step 816, the separated groups are assigned to the appropriate objects from the previous motion image. In step 812, after step 816, the objects history data is updated so that all groups in the current motion image have their center coordinates (x,y) used to update the position of the objects being tracked.
Looking back at
In other embodiments, each object can correlate to an image being displayed on a monitor as part of a video game or other software application. When any of the objects move, application 196 will update the positions of the images on the monitor for the object that moved. For example, if a person moves, the person's avatar in the video game may move. If person throws the ball, an image of the ball may move in the video game. There are many different ways an application can update itself based on the motion of the tracked objects. No particular way for updating the application is required for the technology described herein.
The object history data may also incorporate information about neighboring objects or the structure of a larger object provided by an external system (e.g. structure data 192). For example, if a moving object is identified to be the left arm of a human body or a human head, the system can infer that a certain set of pixels pertains to the left hand. Other variations can also be implemented.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims. It is intended that the scope of the technology be defined by the claims appended hereto.
|Cited Patent||Filing date||Publication date||Applicant||Title|
|US4627620||26 Dec 1984||9 Dec 1986||Yang John P||Electronic athlete trainer for improving skills in reflex, speed and accuracy|
|US4630910||16 Feb 1984||23 Dec 1986||Robotic Vision Systems, Inc.||Method of measuring in three-dimensions at high speed|
|US4645458||15 Apr 1985||24 Feb 1987||Harald Phillip||Athletic evaluation and training apparatus|
|US4695953||14 Apr 1986||22 Sep 1987||Blair Preston E||TV animation interactively controlled by the viewer|
|US4702475||25 Jul 1986||27 Oct 1987||Innovating Training Products, Inc.||Sports technique and reaction training system|
|US4711543||29 Jan 1987||8 Dec 1987||Blair Preston E||TV animation interactively controlled by the viewer|
|US4751642||29 Aug 1986||14 Jun 1988||Silva John M||Interactive sports simulation system with physiological sensing and psychological conditioning|
|US4796997||21 May 1987||10 Jan 1989||Synthetic Vision Systems, Inc.||Method and system for high-speed, 3-D imaging of an object at a vision station|
|US4809065||1 Dec 1986||28 Feb 1989||Kabushiki Kaisha Toshiba||Interactive system and related method for displaying data to produce a three-dimensional image of an object|
|US4817950||8 May 1987||4 Apr 1989||Goo Paul E||Video game control unit and attitude sensor|
|US4843568||11 Apr 1986||27 Jun 1989||Krueger Myron W||Real time perception of and response to the actions of an unencumbered participant/user|
|US4893183||11 Aug 1988||9 Jan 1990||Carnegie-Mellon University||Robotic vision system|
|US4901362||8 Aug 1988||13 Feb 1990||Raytheon Company||Method of recognizing patterns|
|US4925189||13 Jan 1989||15 May 1990||Braeunig Thomas F||Body-mounted video game exercise device|
|US5101444||18 May 1990||31 Mar 1992||Panacea, Inc.||Method and apparatus for high speed object location|
|US5148154||4 Dec 1990||15 Sep 1992||Sony Corporation Of America||Multi-dimensional user interface|
|US5184295||16 Oct 1989||2 Feb 1993||Mann Ralph V||System and method for teaching physical skills|
|US5229754||11 Feb 1991||20 Jul 1993||Yazaki Corporation||Automotive reflection type display apparatus|
|US5229756||14 May 1992||20 Jul 1993||Yamaha Corporation||Image control apparatus|
|US5239463||9 Dec 1991||24 Aug 1993||Blair Preston E||Method and apparatus for player interaction with animated characters and objects|
|US5239464||9 Dec 1991||24 Aug 1993||Blair Preston E||Interactive video system providing repeated switching of multiple tracks of actions sequences|
|US5288078||16 Jul 1992||22 Feb 1994||David G. Capper||Control interface apparatus|
|US5295491||26 Sep 1991||22 Mar 1994||Sam Technology, Inc.||Non-invasive human neurocognitive performance capability testing method and system|
|US5320538||23 Sep 1992||14 Jun 1994||Hughes Training, Inc.||Interactive aircraft training system and method|
|US5347306||17 Dec 1993||13 Sep 1994||Mitsubishi Electric Research Laboratories, Inc.||Animated electronic meeting place|
|US5385519||19 Apr 1994||31 Jan 1995||Hsu; Chi-Hsueh||Running machine|
|US5405152||8 Jun 1993||11 Apr 1995||The Walt Disney Company||Method and apparatus for an interactive video game with physical feedback|
|US5417210||27 May 1992||23 May 1995||International Business Machines Corporation||System and method for augmentation of endoscopic surgery|
|US5423554||24 Sep 1993||13 Jun 1995||Metamedia Ventures, Inc.||Virtual reality game method and apparatus|
|US5454043||30 Jul 1993||26 Sep 1995||Mitsubishi Electric Research Laboratories, Inc.||Dynamic and static hand gesture recognition through low-level image analysis|
|US5469740||2 Dec 1992||28 Nov 1995||Impulse Technology, Inc.||Interactive video testing and training system|
|US5495576||11 Jan 1993||27 Feb 1996||Ritchey; Kurtis J.||Panoramic image based virtual reality/telepresence audio-visual system and method|
|US5516105||6 Oct 1994||14 May 1996||Exergame, Inc.||Acceleration activated joystick|
|US5524637||29 Jun 1994||11 Jun 1996||Erickson; Jon W.||Interactive system for measuring physiological exertion|
|US5534917||9 May 1991||9 Jul 1996||Very Vivid, Inc.||Video image based control system|
|US5563988||1 Aug 1994||8 Oct 1996||Massachusetts Institute Of Technology||Method and system for facilitating wireless, full-body, real-time user interaction with a digitally represented visual environment|
|US5577981||4 Aug 1995||26 Nov 1996||Jarvik; Robert||Virtual reality exercise machine and computer controlled video system|
|US5580249||14 Feb 1994||3 Dec 1996||Sarcos Group||Apparatus for simulating mobility of a human|
|US5594469||21 Feb 1995||14 Jan 1997||Mitsubishi Electric Information Technology Center America Inc.||Hand gesture machine control system|
|US5597309||28 Mar 1994||28 Jan 1997||Riess; Thomas||Method and apparatus for treatment of gait problems associated with parkinson's disease|
|US5616078||27 Dec 1994||1 Apr 1997||Konami Co., Ltd.||Motion-controlled video entertainment system|
|US5617312||18 Nov 1994||1 Apr 1997||Hitachi, Ltd.||Computer system that enters control information by means of video camera|
|US5638300||5 Dec 1994||10 Jun 1997||Johnson; Lee E.||Golf swing analysis system|
|US5641288||11 Jan 1996||24 Jun 1997||Zaenglein, Jr.; William G.||Shooting simulating process and training device using a virtual reality display screen|
|US5682196||22 Jun 1995||28 Oct 1997||Actv, Inc.||Three-dimensional (3D) video presentation system providing interactive 3D presentation with personalized audio responses for multiple viewers|
|US5682229||14 Apr 1995||28 Oct 1997||Schwartz Electro-Optics, Inc.||Laser range camera|
|US5690582||1 Jun 1995||25 Nov 1997||Tectrix Fitness Equipment, Inc.||Interactive exercise apparatus|
|US5703367||8 Dec 1995||30 Dec 1997||Matsushita Electric Industrial Co., Ltd.||Human occupancy detection method and system for implementing the same|
|US5704837||25 Mar 1994||6 Jan 1998||Namco Ltd.||Video game steering system causing translation, rotation and curvilinear motion on the object|
|US5715834||16 May 1995||10 Feb 1998||Scuola Superiore Di Studi Universitari & Di Perfezionamento S. Anna||Device for monitoring the configuration of a distal physiological unit for use, in particular, as an advanced interface for machine and computers|
|US5875108||6 Jun 1995||23 Feb 1999||Hoffberg; Steven M.||Ergonomic man-machine interface incorporating adaptive pattern recognition based control system|
|US5877803||7 Apr 1997||2 Mar 1999||Tritech Mircoelectronics International, Ltd.||3-D image detector|
|US5912700||10 Jan 1996||15 Jun 1999||Fox Sports Productions, Inc.||System for enhancing the television presentation of an object at a sporting event|
|US5913727||13 Jun 1997||22 Jun 1999||Ahdoot; Ned||Interactive movement and contact simulation game|
|US5933125||27 Nov 1995||3 Aug 1999||Cae Electronics, Ltd.||Method and apparatus for reducing instability in the display of a virtual environment|
|US5980256||13 Feb 1996||9 Nov 1999||Carmein; David E. E.||Virtual reality system with enhanced sensory apparatus|
|US5989157||11 Jul 1997||23 Nov 1999||Walton; Charles A.||Exercising system with electronic inertial game playing|
|US5995649||22 Sep 1997||30 Nov 1999||Nec Corporation||Dual-input image processor for recognizing, isolating, and displaying specific objects from the input images|
|US6005548||14 Aug 1997||21 Dec 1999||Latypov; Nurakhmed Nurislamovich||Method for tracking and displaying user's spatial position and orientation, a method for representing virtual reality for a user, and systems of embodiment of such methods|
|US6009210||5 Mar 1997||28 Dec 1999||Digital Equipment Corporation||Hands-free interface to a virtual reality environment using head tracking|
|US6054991||29 Jul 1994||25 Apr 2000||Texas Instruments Incorporated||Method of modeling player position and movement in a virtual reality system|
|US6066075||29 Dec 1997||23 May 2000||Poulton; Craig K.||Direct feedback controller for user interaction|
|US6072494||15 Oct 1997||6 Jun 2000||Electric Planet, Inc.||Method and apparatus for real-time gesture recognition|
|US6073489||3 Mar 1998||13 Jun 2000||French; Barry J.||Testing and training system for assessing the ability of a player to complete a task|
|US6077201||12 Jun 1998||20 Jun 2000||Cheng; Chau-Yang||Exercise bicycle|
|US6098458||6 Nov 1995||8 Aug 2000||Impulse Technology, Ltd.||Testing and training system for assessing movement and agility skills without a confining field|
|US6100896||24 Mar 1997||8 Aug 2000||Mitsubishi Electric Information Technology Center America, Inc.||System for designing graphical multi-participant environments|
|US6101289||15 Oct 1997||8 Aug 2000||Electric Planet, Inc.||Method and apparatus for unencumbered capture of an object|
|US6128003||22 Dec 1997||3 Oct 2000||Hitachi, Ltd.||Hand gesture recognition system and method|
|US6130677||15 Oct 1997||10 Oct 2000||Electric Planet, Inc.||Interactive computer vision system|
|US6133946||11 Mar 1998||17 Oct 2000||Sportvision, Inc.||System for determining the position of an object|
|US6141463||3 Dec 1997||31 Oct 2000||Electric Planet Interactive||Method and system for estimating jointed-figure configurations|
|US6147678||9 Dec 1998||14 Nov 2000||Lucent Technologies Inc.||Video hand image-three-dimensional computer interface with multiple degrees of freedom|
|US6152856||8 May 1997||28 Nov 2000||Real Vision Corporation||Real time simulation using position sensing|
|US6159100||23 Apr 1998||12 Dec 2000||Smith; Michael D.||Virtual reality game|
|US6173066||21 May 1997||9 Jan 2001||Cybernet Systems Corporation||Pose determination and tracking by matching 3D objects to a 2D sensor|
|US6181343||23 Dec 1997||30 Jan 2001||Philips Electronics North America Corp.||System and method for permitting three-dimensional navigation through a virtual reality environment using camera-based gesture inputs|
|US6188777||22 Jun 1998||13 Feb 2001||Interval Research Corporation||Method and apparatus for personnel detection and tracking|
|US6215890||25 Sep 1998||10 Apr 2001||Matsushita Electric Industrial Co., Ltd.||Hand gesture recognizing device|
|US6215898||15 Apr 1997||10 Apr 2001||Interval Research Corporation||Data processing system and method|
|US6226396||31 Jul 1998||1 May 2001||Nec Corporation||Object extraction method and system|
|US6229913||7 Jun 1995||8 May 2001||The Trustees Of Columbia University In The City Of New York||Apparatus and methods for determining the three-dimensional shape of an object using active illumination and relative blurring in two-images due to defocus|
|US6256033 *||10 Aug 1999||3 Jul 2001||Electric Planet||Method and apparatus for real-time gesture recognition|
|US6256400||28 Sep 1999||3 Jul 2001||Matsushita Electric Industrial Co., Ltd.||Method and device for segmenting hand gestures|
|US6283860||14 Aug 2000||4 Sep 2001||Philips Electronics North America Corp.||Method, system, and program for gesture based option selection|
|US6289112||25 Feb 1998||11 Sep 2001||International Business Machines Corporation||System and method for determining block direction in fingerprint images|
|US6299308||31 Mar 2000||9 Oct 2001||Cybernet Systems Corporation||Low-cost non-imaging eye tracker system for computer control|
|US6308565||15 Oct 1998||30 Oct 2001||Impulse Technology Ltd.||System and method for tracking and assessing movement skills in multidimensional space|
|US6316934||30 Jun 1999||13 Nov 2001||Netmor Ltd.||System for three dimensional positioning and tracking|
|US6363160||22 Jan 1999||26 Mar 2002||Intel Corporation||Interface using pattern recognition and tracking|
|US6384819||15 Oct 1998||7 May 2002||Electric Planet, Inc.||System and method for generating an animatable character|
|US6411744||15 Oct 1998||25 Jun 2002||Electric Planet, Inc.||Method and apparatus for performing a clean background subtraction|
|US6430997||5 Sep 2000||13 Aug 2002||Trazer Technologies, Inc.||System and method for tracking and assessing movement skills in multidimensional space|
|US6476834||28 May 1999||5 Nov 2002||International Business Machines Corporation||Dynamic creation of selectable items on surfaces|
|US6496598||1 Mar 2000||17 Dec 2002||Dynamic Digital Depth Research Pty. Ltd.||Image processing method and apparatus|
|US6503195||24 May 1999||7 Jan 2003||University Of North Carolina At Chapel Hill||Methods and systems for real-time structured light depth extraction and endoscope using real-time structured light depth extraction|
|US6512838||5 Oct 2000||28 Jan 2003||Canesta, Inc.||Methods for enhancing performance and data acquired from three-dimensional image systems|
|US6539931||16 Apr 2001||1 Apr 2003||Koninklijke Philips Electronics N.V.||Ball throwing assistant|
|US6570555||30 Dec 1998||27 May 2003||Fuji Xerox Co., Ltd.||Method and apparatus for embodied conversational characters with multimodal input/output in an interface device|
|US6633294||9 Mar 2001||14 Oct 2003||Seth Rosenthal||Method and apparatus for using captured high density motion for animation|
|US6640202||25 May 2000||28 Oct 2003||International Business Machines Corporation||Elastic sensor mesh system for 3-dimensional measurement, mapping and kinematics applications|
|US6658136||6 Dec 1999||2 Dec 2003||Microsoft Corporation||System and process for locating and tracking a person or object in a scene using a series of range images|
|US6661918||3 Dec 1999||9 Dec 2003||Interval Research Corporation||Background estimation and segmentation based on range and color|
|US6674877||3 Feb 2000||6 Jan 2004||Microsoft Corporation||System and method for visually tracking occluded objects in real time|
|US6681031||10 Aug 1999||20 Jan 2004||Cybernet Systems Corporation||Gesture-controlled interfaces for self-service machines and other applications|
|US6714665||3 Dec 1996||30 Mar 2004||Sarnoff Corporation||Fully automated iris recognition system utilizing wide and narrow fields of view|
|US6728637||22 Jun 2001||27 Apr 2004||Sportvision, Inc.||Track model constraint for GPS position|
|US6731799||1 Jun 2000||4 May 2004||University Of Washington||Object segmentation with background extraction and moving boundary techniques|
|US6738066||30 Jul 1999||18 May 2004||Electric Plant, Inc.||System, method and article of manufacture for detecting collisions between video images generated by a camera and an object depicted on a display|
|US6765726||17 Jul 2002||20 Jul 2004||Impluse Technology Ltd.||System and method for tracking and assessing movement skills in multidimensional space|
|US6788809||30 Jun 2000||7 Sep 2004||Intel Corporation||System and method for gesture recognition in three dimensions using stereo imaging and color vision|
|US6801637||22 Feb 2001||5 Oct 2004||Cybernet Systems Corporation||Optical body tracker|
|US6873723||30 Jun 1999||29 Mar 2005||Intel Corporation||Segmenting three-dimensional video images using stereo|
|US6876496||9 Jul 2004||5 Apr 2005||Impulse Technology Ltd.||System and method for tracking and assessing movement skills in multidimensional space|
|US6937742||28 Sep 2001||30 Aug 2005||Bellsouth Intellectual Property Corporation||Gesture activated home appliance|
|US6950534||16 Jan 2004||27 Sep 2005||Cybernet Systems Corporation||Gesture-controlled interfaces for self-service machines and other applications|
|US7003134||8 Mar 2000||21 Feb 2006||Vulcan Patents Llc||Three dimensional object pose estimation which employs dense depth information|
|US7003136||26 Apr 2002||21 Feb 2006||Hewlett-Packard Development Company, L.P.||Plan-view projections of depth image data for object tracking|
|US7036094||31 Mar 2000||25 Apr 2006||Cybernet Systems Corporation||Behavior recognition system|
|US7038855||5 Apr 2005||2 May 2006||Impulse Technology Ltd.||System and method for tracking and assessing movement skills in multidimensional space|
|US7039676||31 Oct 2000||2 May 2006||International Business Machines Corporation||Using video image analysis to automatically transmit gestures over a network in a chat or instant messaging session|
|US7042440||21 Jul 2003||9 May 2006||Pryor Timothy R||Man machine interfaces and applications|
|US7050606||1 Nov 2001||23 May 2006||Cybernet Systems Corporation||Tracking and gesture recognition system particularly suited to vehicular control applications|
|US7058204||26 Sep 2001||6 Jun 2006||Gesturetek, Inc.||Multiple camera control system|
|US7060957||26 Mar 2001||13 Jun 2006||Csem Centre Suisse D'electronique Et Microtechinique Sa||Device and method for spatially resolved photodetection and demodulation of modulated electromagnetic waves|
|US7075556||21 Oct 1999||11 Jul 2006||Sportvision, Inc.||Telestrator system|
|US7113918||1 Aug 1999||26 Sep 2006||Electric Planet, Inc.||Method for video enabled electronic commerce|
|US7121946||29 Jun 2001||17 Oct 2006||Cybernet Systems Corporation||Real-time head tracking system for computer games and other applications|
|US7170492||18 Mar 2005||30 Jan 2007||Reactrix Systems, Inc.||Interactive video display system|
|US7184048||18 Oct 2001||27 Feb 2007||Electric Planet, Inc.||System and method for generating an animatable character|
|US7202898||16 Dec 1998||10 Apr 2007||3Dv Systems Ltd.||Self gating photosurface|
|US7222078||10 Dec 2003||22 May 2007||Ferrara Ethereal Llc||Methods and systems for gathering information from units of a commodity across a network|
|US7227526||23 Jul 2001||5 Jun 2007||Gesturetek, Inc.||Video-based image control system|
|US7259747||28 May 2002||21 Aug 2007||Reactrix Systems, Inc.||Interactive video display system|
|US7308112||12 May 2005||11 Dec 2007||Honda Motor Co., Ltd.||Sign based human-machine interaction|
|US7317836||17 Mar 2006||8 Jan 2008||Honda Motor Co., Ltd.||Pose estimation based on critical point analysis|
|US7348963||5 Aug 2005||25 Mar 2008||Reactrix Systems, Inc.||Interactive video display system|
|US7359121||1 May 2006||15 Apr 2008||Impulse Technology Ltd.||System and method for tracking and assessing movement skills in multidimensional space|
|US7366325||12 Oct 2004||29 Apr 2008||Honda Motor Co., Ltd.||Moving object detection using low illumination depth capable computer vision|
|US7367887||7 Jul 2003||6 May 2008||Namco Bandai Games Inc.||Game apparatus, storage medium, and computer program that adjust level of game difficulty|
|US7379563||15 Apr 2005||27 May 2008||Gesturetek, Inc.||Tracking bimanual movements|
|US7379566||6 Jan 2006||27 May 2008||Gesturetek, Inc.||Optical flow based tilt sensor|
|US7389591||17 May 2006||24 Jun 2008||Gesturetek, Inc.||Orientation-sensitive signal output|
|US7412077||29 Dec 2006||12 Aug 2008||Motorola, Inc.||Apparatus and methods for head pose estimation and head gesture detection|
|US7421093||19 Dec 2005||2 Sep 2008||Gesturetek, Inc.||Multiple camera control system|
|US7430312||9 Jan 2006||30 Sep 2008||Gesturetek, Inc.||Creating 3D images of objects by illuminating with infrared patterns|
|US7436496||28 Jan 2004||14 Oct 2008||National University Corporation Shizuoka University||Distance image sensor|
|US7450736||26 Oct 2006||11 Nov 2008||Honda Motor Co., Ltd.||Monocular tracking of 3D human motion with a coordinated mixture of factor analyzers|
|US7452275||25 Jun 2002||18 Nov 2008||Konami Digital Entertainment Co., Ltd.||Game device, game controlling method and program|
|US7460690||14 Sep 2005||2 Dec 2008||Cybernet Systems Corporation||Gesture-controlled interfaces for self-service machines and other applications|
|US7489812||7 Jun 2002||10 Feb 2009||Dynamic Digital Depth Research Pty Ltd.||Conversion and encoding techniques|
|US7536032||25 Oct 2004||19 May 2009||Reactrix Systems, Inc.||Method and system for processing captured image information in an interactive video display system|
|US7555142||31 Oct 2007||30 Jun 2009||Gesturetek, Inc.||Multiple camera control system|
|US7560701||11 Aug 2006||14 Jul 2009||Mesa Imaging Ag||Highly sensitive, fast pixel for use in an image sensor|
|US7570805||23 Apr 2008||4 Aug 2009||Gesturetek, Inc.||Creating 3D images of objects by illuminating with infrared patterns|
|US7574020||7 Apr 2008||11 Aug 2009||Gesturetek, Inc.||Detecting and tracking objects in images|
|US7576727||15 Dec 2003||18 Aug 2009||Matthew Bell||Interactive directed light/sound system|
|US7590262||21 Apr 2008||15 Sep 2009||Honda Motor Co., Ltd.||Visual tracking using depth data|
|US7593552||22 Mar 2004||22 Sep 2009||Honda Motor Co., Ltd.||Gesture recognition apparatus, gesture recognition method, and gesture recognition program|
|US7598942||8 Feb 2006||6 Oct 2009||Oblong Industries, Inc.||System and method for gesture based control system|
|US7607509||13 Jan 2003||27 Oct 2009||Iee International Electronics & Engineering S.A.||Safety device for a vehicle|
|US7620202||14 Jun 2004||17 Nov 2009||Honda Motor Co., Ltd.||Target orientation estimation using depth sensing|
|US7668340||2 Dec 2008||23 Feb 2010||Cybernet Systems Corporation||Gesture-controlled interfaces for self-service machines and other applications|
|US7680298||8 Oct 2008||16 Mar 2010||At&T Intellectual Property I, L. P.||Methods, systems, and products for gesture-activated appliances|
|US7683954||27 Sep 2007||23 Mar 2010||Brainvision Inc.||Solid-state image sensor|
|US7684592||14 Jan 2008||23 Mar 2010||Cybernet Systems Corporation||Realtime object tracking system|
|US7701439||13 Jul 2006||20 Apr 2010||Northrop Grumman Corporation||Gesture recognition simulation system and method|
|US7702130||29 Sep 2005||20 Apr 2010||Electronics And Telecommunications Research Institute||User interface apparatus using hand gesture recognition and method thereof|
|US7704135||23 Aug 2005||27 Apr 2010||Harrison Jr Shelton E||Integrated game system, method, and device|
|US7710391||20 Sep 2004||4 May 2010||Matthew Bell||Processing an image utilizing a spatially varying pattern|
|US7729530||3 Mar 2007||1 Jun 2010||Sergey Antonov||Method and apparatus for 3-D data input to a personal computer with a multimedia oriented operating system|
|US7746345||27 Feb 2007||29 Jun 2010||Hunter Kevin L||System and method for generating an animatable character|
|US7760182||21 Aug 2006||20 Jul 2010||Subutai Ahmad||Method for video enabled electronic commerce|
|US7809167||19 May 2009||5 Oct 2010||Matthew Bell||Method and system for processing captured image information in an interactive video display system|
|US7834846||21 Aug 2006||16 Nov 2010||Matthew Bell||Interactive video display system|
|US7852262||15 Aug 2008||14 Dec 2010||Cybernet Systems Corporation||Wireless mobile indoor/outdoor tracking system|
|US7898522||1 Jun 2007||1 Mar 2011||Gesturetek, Inc.||Video-based image control system|
|US8035612||20 Sep 2004||11 Oct 2011||Intellectual Ventures Holding 67 Llc||Self-contained interactive video display system|
|US8035614||30 Oct 2007||11 Oct 2011||Intellectual Ventures Holding 67 Llc||Interactive video window|
|US8035624||30 Oct 2007||11 Oct 2011||Intellectual Ventures Holding 67 Llc||Computer vision based touch screen|
|US8072470||29 May 2003||6 Dec 2011||Sony Computer Entertainment Inc.||System and method for providing a real-time three-dimensional interactive environment|
|US8374423||2 Mar 2012||12 Feb 2013||Microsoft Corporation||Motion detection using depth images|
|US20030219146||23 May 2002||27 Nov 2003||Jepson Allan D.||Visual motion analysis method for detecting arbitrary numbers of moving objects in image sequences|
|US20050058337||14 Jun 2004||17 Mar 2005||Kikuo Fujimura||Target orientation estimation using depth sensing|
|US20050190972||11 Feb 2005||1 Sep 2005||Thomas Graham A.||System and method for position determination|
|US20070110298 *||14 Nov 2005||17 May 2007||Microsoft Corporation||Stereo video for gaming|
|US20080026838||21 Aug 2006||31 Jan 2008||Dunstan James E||Multi-player non-role-playing virtual world games: method for two-way interaction between participants and multi-player virtual world games|
|US20080152191||9 Oct 2007||26 Jun 2008||Honda Motor Co., Ltd.||Human Pose Estimation and Tracking Using Label Assignment|
|US20080166045||1 Mar 2006||10 Jul 2008||Li-Qun Xu||Method of Tracking Objects in a Video Sequence|
|US20090141933||4 Dec 2008||4 Jun 2009||Sony Corporation||Image processing apparatus and method|
|US20090175540||19 Dec 2008||9 Jul 2009||Honda Motor Co., Ltd.||Controlled human pose estimation from depth image streams|
|US20090221368||26 Apr 2009||3 Sep 2009||Ailive Inc.,||Method and system for creating a shared game space for a networked game|
|US20110150271||18 Dec 2009||23 Jun 2011||Microsoft Corporation||Motion detection using depth images|
|USRE42256||9 Jan 2009||29 Mar 2011||Elet Systems L.L.C.||Method and apparatus for performing a clean background subtraction|
|CN101254344B||18 Apr 2008||16 Jun 2010||李刚||Game device of field orientation corresponding with display screen dot array in proportion and method|
|EP0583061A2||5 Jul 1993||16 Feb 1994||The Walt Disney Company||Method and apparatus for providing enhanced graphics in a virtual world|
|JP08044490A1||Title not available|
|WO2093/10708A1||Title not available|
|WO2097/17598A1||Title not available|
|WO2099/44698A1||Title not available|
|WO2009059065A1||30 Oct 2008||7 May 2009||Hewlett-Packard Development Company, L.P.||Interactive display system with collaborative gesture detection|
|1||"Simulation and Training", 1994, Division Incorporated.|
|2||"Virtual High Anxiety", Tech Update, Aug. 1995, pp. 22.|
|3||Aggarwal et al., "Human Motion Analysis: A Review", IEEE Nonrigid and Articulated Motion Workshop, 1997, University of Texas at Austin, Austin, TX.|
|4||Aggarwal, "Human Motion Analysis: A Review," Published Date: Mar. 1999 http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.50.6195&rep=rep1&type=pdf.|
|5||Azarbayejani et al., "Visually Controlled Graphics", Jun. 1993, vol. 15, No. 6, IEEE Transactions on Pattern Analysis and Machine Intelligence.|
|6||Breen et al., "Interactive Occlusion and Collusion of Real and Virtual Objects in Augmented Reality", Technical Report ECRC-95-02, 1995, European Computer-Industry Research Center GmbH, Munich, Germany.|
|7||Brogan et al., "Dynamically Simulated Characters in Virtual Environments", Sep./Oct. 1998, pp. 2-13, vol. 18, Issue 5, IEEE Computer Graphics and Applications.|
|8||English Machine-translation of Japanese Publication No. JP08-044490 published on Feb. 16, 1996.|
|9||Fisher et al., "Virtual Environment Display System", ACM Workshop on Interactive 3D Graphics, Oct. 1986, Chapel Hill, NC.|
|10||Freeman et al., "Television Control by Hand Gestures", Dec. 1994, Mitsubishi Electric Research Laboratories, TR94-24, Caimbridge, MA.|
|11||Granieri et al., "Simulating Humans in VR", The British Computer Society, Oct. 1994, Academic Press.|
|12||Hasegawa et al., "Human-Scale Haptic Interaction with a Reactive Virtual Human in a Real-Time Physics Simulator", Jul. 2006, vol. 4, No. 3, Article 6C, ACM Computers in Entertainment, New York, NY.|
|13||He, "Generation of Human Body Models", Apr. 2005, University of Auckland, New Zealand.|
|14||Hongo et al., "Focus of Attention for Face and Hand Gesture Recognition Using Multiple Cameras", Mar. 2000, pp. 156-161, 4th IEEE International Conference on Automatic Face and Gesture Recognition, Grenoble, France.|
|15||Isard et al., "Condensation-Conditional Density Propagation for Visual Tracking", 1998, pp. 5-28, International Journal of Computer Vision 29(1), Netherlands.|
|16||Isard et al., "Condensation—Conditional Density Propagation for Visual Tracking", 1998, pp. 5-28, International Journal of Computer Vision 29(1), Netherlands.|
|17||Kam, "A Real-time 3D Motion Tracking System," Published Date: Apr. 1993 https://circle.ubc.ca/bitstream/2429/2545/3/ubc-1993-spring-kam-johnny.pdf.|
|18||Kam, "A Real-time 3D Motion Tracking System," Published Date: Apr. 1993 https://circle.ubc.ca/bitstream/2429/2545/3/ubc—1993—spring—kam—johnny.pdf.|
|19||Kanade et al., "A Stereo Machine for Video-rate Dense Depth Mapping and Its New Applications", IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1996, pp. 196-202,The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA.|
|20||Kohler, "Special Topics of Gesture Recognition Applied in Intelligent Home Environments", In Proceedings of the Gesture Workshop, 1998, pp. 285-296, Germany.|
|21||Kohler, "Technical Details and Ergonomical Aspects of Gesture Recognition applied in Intelligent Home Environments", 1997, Germany.|
|22||Kohler, "Vision Based Remote Control in Intelligent Home Environments", University of Erlangen-Nuremberg/Germany, 1996, pp. 147-154, Germany.|
|23||Livingston, "Vision-based Tracking with Dynamic Structured Light for Video See-through Augmented Reality", 1998, University of North Carolina at Chapel Hill, North Carolina, USA.|
|24||Micilotta, "The Tracking of Hands for the Development of a Gesture Recognition Algorithm," Published Date: Oct. 18, 2000, http://www.amicilotta.airpost.net/documents/micilotta-undergrad-dissertation.pdf.|
|25||Micilotta, "The Tracking of Hands for the Development of a Gesture Recognition Algorithm," Published Date: Oct. 18, 2000, http://www.amicilotta.airpost.net/documents/micilotta—undergrad—dissertation.pdf.|
|26||Miyagawa et al., "CCD-Based Range Finding Sensor", Oct. 1997, pp. 1648-1652, vol. 44 No. 10, IEEE Transactions on Electron Devices.|
|27||Notice of Allowance dated Oct. 18, 2012, in U.S. Appl. No. 13/410,546, filed Mar. 2, 2012.|
|28||Office Action dated Jun. 1, 2012, in U.S. Appl. No. 13/410,546, filed Mar. 2, 2012.|
|29||Pavlovic et al., "Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review", Jul. 1997, pp. 677-695, vol. 19, No. 7, IEEE Transactions on Pattern Analysis and Machine Intelligence.|
|30||Qian et al., "A Gesture-Driven Multimodal Interactive Dance System", Jun. 2004, pp. 1579-1582, IEEE International Conference on Multimedia and Expo (ICME), Taipei, Taiwan.|
|31||Rosenhahn et al., "Automatic Human Model Generation", 2005, pp. 41-48, University of Auckland (CITR), New Zealand.|
|32||Rybski, "Cameo: Camera Assisted Meeting Event Observer," Published Date: Apr. 2004 http://www.cs.cmu.edu/~mmv/papers/04icra-cameo.pdf.|
|33||Rybski, "Cameo: Camera Assisted Meeting Event Observer," Published Date: Apr. 2004 http://www.cs.cmu.edu/˜mmv/papers/04icra-cameo.pdf.|
|34||Shao et al., "An Open System Architecture for a Multimedia and Multimodal User Interface", Aug. 24, 1998, Japanese Society for Rehabilitation of Persons with Disabilities (JSRPD), Japan.|
|35||Sheridan et al., "Virtual Reality Check", Technology Review, Oct. 1993, pp. 22-28, vol. 96, No. 7.|
|36||Shivappa, et al., "Person Tracking With Audio-visual Cues Using the Iterative Decoding Framework," IEEE 5th International Conference on Advanced Video and Signal Based Surveillance, 2008, pp. 260-267.|
|37||Stevens, "Flights into Virtual Reality Treating Real-World Disorders", Science Psychology.|
|38||Toyama, et al., "Probabilistic Tracking in a Metric Space," Eighth International Conference on Computer Vision, Vancouver, Canada, vol. 2, Jul. 2001, 8 pages.|
|39||Wren et al., "Pfinder: Real-Time Tracking of the Human Body", MIT Media Laboratory Perceptual Computing Section Technical Report No. 353, Jul. 1997, vol. 19, No. 7, pp. 780-785, IEEE Transactions on Pattern Analysis and Machine Intelligence, Caimbridge, MA.|
|40||Zhao, "Dressed Human Modeling, Detection, and Parts Localization", 2001, The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA.|
|Citing Patent||Filing date||Publication date||Applicant||Title|
|US9257061||14 Mar 2014||9 Feb 2016||The Coca-Cola Company||Display devices|
|US9269283||14 Mar 2014||23 Feb 2016||The Coca-Cola Company||Display devices|
|US9569688||22 Jun 2015||14 Feb 2017||Hanwha Techwin Co., Ltd.||Apparatus and method of detecting motion mask|
|US9628843 *||21 Nov 2011||18 Apr 2017||Microsoft Technology Licensing, Llc||Methods for controlling electronic devices using gestures|
|US9640118||14 Jan 2016||2 May 2017||The Coca-Cola Company||Display devices|
|Cooperative Classification||G06T7/215, G06T7/254, G06K9/00, G06K9/00335, G06T2207/10028|
|6 Feb 2013||AS||Assignment|
Owner name: MICROSOFT CORPORATION, WASHINGTON
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Owner name: MICROSOFT TECHNOLOGY LICENSING, LLC, WASHINGTON
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